Search ga_ls7e_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-09-24 09:50:39	ga_ls7e_ard_3-2-0_106071_2021-09-24_final
2021-09-24 09:53:51	ga_ls7e_ard_3-2-0_106079_2021-09-24_final
2021-09-25 10:35:01	ga_ls7e_ard_3-2-0_113074_2021-09-25_final
2021-09-25 10:37:25	ga_ls7e_ard_3-2-0_113080_2021-09-25_final
2021-09-26 09:37:19	ga_ls7e_ard_3-2-0_104069_2021-09-26_final
2021-09-26 09:40:06	ga_ls7e_ard_3-2-0_104076_2021-09-26_final
2021-09-29 10:11:32	ga_ls7e_ard_3-2-0_109078_2021-09-29_final
2021-10-01 09:59:24	ga_ls7e_ard_3-2-0_107079_2021-10-01_final
2021-10-02 09:02:54	ga_ls7e_ard_3-2-0_098077_2021-10-01_final
2021-10-09 09:10:04	ga_ls7e_ard_3-2-0_099081_2021-10-08_final
2021-10-09 10:48:08	ga_ls7e_ard_3-2-0_115079_2021-10-09_final
2021-10-10 09:48:03	ga_ls7e_ard_3-2-0_106068_2021-10-10_final
2021-10-11 08:57:55	ga_ls7e_ard_3-2-0_097082_2021-10-10_final
2021-10-11 10:35:12	ga_ls7e_ard_3-2-0_113078_2021-10-11_final
2021-10-12 09:35:54	ga_ls7e_ard_3-2-0_104069_2021-10-12_final
2021-10-22 10:15:41	ga_ls7e_ard_3-2-0_110078_2021-10-22_final
2021-10-23 09:21:58	ga_ls7e_ard_3-2-0_101083_2021-10-22_final
2021-10-24 10:04:20	ga_ls7e_ard_3-2-0_108081_2021-10-24_final
2021-10-25 09:08:13	ga_ls7e_ard_3-2-0_099080_2021-10-24_final
2021-10-25 10:45:30	ga_ls7e_ard_3-2-0_115076_2021-10-25_final
2021-10-28 09:34:51	ga_ls7e_ard_3-2-0_104070_2021-10-28_final
2021-10-29 10:20:49	ga_ls7e_ard_3-2-0_111077_2021-10-29_final
2021-11-03 08:58:49	ga_ls7e_ard_3-2-0_098074_2021-11-02_final
2021-11-03 09:01:12	ga_ls7e_ard_3-2-0_098080_2021-11-02_final
2021-11-07 10:15:47	ga_ls7e_ard_3-2-0_110082_2021-11-07_final
2021-11-11 08:14:12	ga_ls7e_ard_3-2-0_090088_2021-11-10_final
2021-11-13 09:36:32	ga_ls7e_ard_3-2-1_104078_2021-11-13_final
2021-11-14 10:20:53	ga_ls7e_ard_3-2-1_111081_2021-11-14_final
2021-11-18 09:52:59	ga_ls7e_ard_3-2-1_107074_2021-11-18_final
2021-11-19 08:57:16	ga_ls7e_ard_3-2-1_098074_2021-11-18_final
2021-11-22 09:26:40	ga_ls7e_ard_3-2-1_103071_2021-11-21_final
2021-11-23 08:33:21	ga_ls7e_ard_3-2-1_094077_2021-11-22_final
2021-11-26 10:42:51	ga_ls7e_ard_3-2-1_115077_2021-11-26_final
2021-11-30 08:40:28	ga_ls7e_ard_3-2-1_095081_2021-11-29_final
2021-12-03 09:08:42	ga_ls7e_ard_3-2-1_100075_2021-12-02_final
2021-12-03 09:11:53	ga_ls7e_ard_3-2-1_100083_2021-12-02_final
2021-12-04 09:51:28	ga_ls7e_ard_3-2-1_107074_2021-12-04_final
2021-12-12 10:41:20	ga_ls7e_ard_3-2-1_115077_2021-12-12_final
2021-12-17 09:20:31	ga_ls7e_ard_3-2-1_102077_2021-12-16_final
2021-12-22 09:36:35	ga_ls7e_ard_3-2-1_105072_2021-12-22_final
2021-12-24 09:27:37	ga_ls7e_ard_3-2-1_103081_2021-12-23_final
2021-12-30 10:26:49	ga_ls7e_ard_3-2-1_113076_2021-12-30_final
2021-12-31 09:31:06	ga_ls7e_ard_3-2-1_104076_2021-12-31_final
2022-01-03 09:59:41	ga_ls7e_ard_3-2-1_109071_2022-01-03_final
2022-01-03 10:00:29	ga_ls7e_ard_3-2-1_109073_2022-01-03_final
2022-01-06 08:52:37	ga_ls7e_ard_3-2-1_098074_2022-01-05_final
2022-01-06 08:55:00	ga_ls7e_ard_3-2-1_098080_2022-01-05_final
2022-01-08 08:39:40	ga_ls7e_ard_3-2-1_096073_2022-01-07_final
2022-01-10 10:09:59	ga_ls7e_ard_3-2-1_110083_2022-01-10_final
2022-01-11 09:12:41	ga_ls7e_ard_3-2-1_101079_2022-01-10_final
2022-01-13 08:55:21	ga_ls7e_ard_3-2-1_099067_2022-01-12_final
2022-01-13 08:58:32	ga_ls7e_ard_3-2-1_099075_2022-01-12_final
2022-01-13 10:38:37	ga_ls7e_ard_3-2-1_115078_2022-01-13_final
2022-01-14 09:42:54	ga_ls7e_ard_3-2-1_106078_2022-01-14_final
2022-01-16 09:27:34	ga_ls7e_ard_3-2-1_104071_2022-01-15_final
2022-01-22 08:48:43	ga_ls7e_ard_3-2-1_098068_2022-01-21_final
2022-01-22 08:49:54	ga_ls7e_ard_3-2-1_098071_2022-01-21_final
2022-01-22 08:51:06	ga_ls7e_ard_3-2-1_098074_2022-01-21_final
2022-01-22 10:30:23	ga_ls7e_ard_3-2-1_114075_2022-01-22_final
2022-01-23 09:33:28	ga_ls7e_ard_3-2-1_105072_2022-01-23_final
2022-01-24 08:36:57	ga_ls7e_ard_3-2-1_096070_2022-01-23_final
2022-01-27 09:10:21	ga_ls7e_ard_3-2-1_101077_2022-01-26_final
2022-02-06 08:11:56	ga_ls7e_ard_3-2-1_091088_2022-02-05_final
2022-02-07 08:50:42	ga_ls7e_ard_3-2-1_098077_2022-02-06_final
2022-02-07 08:51:30	ga_ls7e_ard_3-2-1_098079_2022-02-06_final
2022-02-07 08:51:54	ga_ls7e_ard_3-2-1_098080_2022-02-06_final
2022-02-08 07:57:23	ga_ls7e_ard_3-2-1_089083_2022-02-07_final
2022-02-08 09:31:52	ga_ls7e_ard_3-2-1_105072_2022-02-08_final
2022-02-08 09:33:04	ga_ls7e_ard_3-2-1_105075_2022-02-08_final
2022-02-10 09:21:18	ga_ls7e_ard_3-2-1_103077_2022-02-09_final
2022-02-11 10:06:03	ga_ls7e_ard_3-2-1_110081_2022-02-11_final
2022-02-12 09:08:19	ga_ls7e_ard_3-2-1_101076_2022-02-11_final
2022-02-14 08:55:21	ga_ls7e_ard_3-2-1_099075_2022-02-13_final
2022-02-15 08:00:50	ga_ls7e_ard_3-2-1_090078_2022-02-14_final
2022-02-21 08:59:40	ga_ls7e_ard_3-2-1_100072_2022-02-20_final
2022-02-23 08:48:19	ga_ls7e_ard_3-2-1_098075_2022-02-22_final
2022-02-23 08:50:18	ga_ls7e_ard_3-2-1_098080_2022-02-22_final
2022-02-28 09:07:58	ga_ls7e_ard_3-2-1_101079_2022-02-27_final
2022-03-04 08:42:04	ga_ls7e_ard_3-2-1_097077_2022-03-03_final
2022-03-04 10:20:56	ga_ls7e_ard_3-2-1_113077_2022-03-04_final
2022-03-06 10:07:35	ga_ls7e_ard_3-2-1_111075_2022-03-06_final
2022-03-09 08:59:18	ga_ls7e_ard_3-2-1_100075_2022-03-08_final
2022-03-09 09:02:54	ga_ls7e_ard_3-2-1_100084_2022-03-08_final
2022-03-10 09:41:16	ga_ls7e_ard_3-2-1_107072_2022-03-10_final
2022-03-11 10:27:37	ga_ls7e_ard_3-2-1_114080_2022-03-11_final
2022-03-12 07:53:01	ga_ls7e_ard_3-2-1_089080_2022-03-11_final
2022-03-12 07:54:13	ga_ls7e_ard_3-2-1_089083_2022-03-11_final
2022-03-12 09:30:18	ga_ls7e_ard_3-2-1_105076_2022-03-12_final
2022-03-15 09:58:54	ga_ls7e_ard_3-2-1_110071_2022-03-15_final
2022-03-20 08:38:28	ga_ls7e_ard_3-2-1_097072_2022-03-19_final
2022-03-23 09:11:05	ga_ls7e_ard_3-2-1_102077_2022-03-22_final
2022-03-24 08:14:10	ga_ls7e_ard_3-2-1_093074_2022-03-23_final
2022-03-24 09:56:39	ga_ls7e_ard_3-2-1_109083_2022-03-24_final
2022-03-26 08:06:25	ga_ls7e_ard_3-2-1_091086_2022-03-25_final
2022-03-27 08:45:59	ga_ls7e_ard_3-2-1_098077_2022-03-26_final
2022-03-28 09:27:33	ga_ls7e_ard_3-2-1_105073_2022-03-27_final
2022-03-29 08:32:14	ga_ls7e_ard_3-2-1_096074_2022-03-28_final
2022-03-31 10:00:34	ga_ls7e_ard_3-2-1_110079_2022-03-31_final
2022-04-02 08:07:56	ga_ls7e_ard_3-2-1_092076_2022-04-01_final
2022-04-02 08:08:20	ga_ls7e_ard_3-2-1_092077_2022-04-01_final

Return to ga_ls7e_ard_3 whole collection overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years